15 January 2023 08:09:41 PM sandia_sgmgg_test(): C++ version. test sandia_sgmgg(). TEST01: Demonstrate naive coefficient calculations. 1) Isotropic grid in 2D: SPARSE_INDEX matrix: Row: 0 1 Col 0: 0 2 1: 0 3 2: 1 1 3: 1 2 4: 2 0 5: 2 1 6: 3 0 COEF vector: 0: -1 1: 1 2: -1 3: 1 4: -1 5: 1 6: 1 --- - Sum: 1 2) Isotropic grid in 3D: SPARSE_INDEX matrix: Row: 0 1 2 Col 0: 0 1 0 1: 0 2 0 2: 0 3 0 3: 1 0 0 4: 1 1 0 5: 1 2 0 6: 2 0 0 7: 2 1 0 8: 3 0 0 9: 0 0 1 10: 0 1 1 11: 0 2 1 12: 1 0 1 13: 1 1 1 14: 2 0 1 15: 0 0 2 16: 0 1 2 17: 1 0 2 18: 0 0 3 COEF vector: 0: 1 1: -2 2: 1 3: 1 4: -2 5: 1 6: -2 7: 1 8: 1 9: 1 10: -2 11: 1 12: -2 13: 1 14: 1 15: -2 16: 1 17: 1 18: 1 --- - Sum: 1 3) Ansotropic grid in 2D: SPARSE_INDEX matrix: Row: 0 1 Col 0: 0 2 1: 1 1 2: 1 2 3: 2 1 4: 3 0 5: 3 1 6: 4 0 7: 5 0 COEF vector: 0: 0 1: -1 2: 1 3: 0 4: -1 5: 1 6: 0 7: 1 --- - Sum: 1 4) Generalized grid in 2D: SPARSE_INDEX matrix: Row: 0 1 Col 0: 0 0 1: 0 1 2: 0 2 3: 0 3 4: 1 0 5: 1 1 6: 2 0 7: 3 0 COEF vector: 0: 0 1: -1 2: 0 3: 1 4: -1 5: 1 6: 0 7: 1 --- - Sum: 1 TEST02: Demonstrate naive neighbor calculations. 1) Isotropic grid in 2D: SPARSE_INDEX matrix: Row: 0 1 Col 0: 0 2 1: 0 3 2: 1 1 3: 1 2 4: 2 0 5: 2 1 6: 3 0 NEIGHBOR matrix: Row: 0 1 Col 0: 1 1 1: 0 0 2: 1 1 3: 0 0 4: 1 1 5: 0 0 6: 0 0 2) Isotropic grid in 3D: SPARSE_INDEX matrix: Row: 0 1 2 Col 0: 0 1 0 1: 0 2 0 2: 0 3 0 3: 1 0 0 4: 1 1 0 5: 1 2 0 6: 2 0 0 7: 2 1 0 8: 3 0 0 9: 0 0 1 10: 0 1 1 11: 0 2 1 12: 1 0 1 13: 1 1 1 14: 2 0 1 15: 0 0 2 16: 0 1 2 17: 1 0 2 18: 0 0 3 NEIGHBOR matrix: Row: 0 1 2 Col 0: 1 1 1 1: 1 1 1 2: 0 0 0 3: 1 1 1 4: 1 1 1 5: 0 0 0 6: 1 1 1 7: 0 0 0 8: 0 0 0 9: 1 1 1 10: 1 1 1 11: 0 0 0 12: 1 1 1 13: 0 0 0 14: 0 0 0 15: 1 1 1 16: 0 0 0 17: 0 0 0 18: 0 0 0 3) Ansotropic grid in 2D: SPARSE_INDEX matrix: Row: 0 1 Col 0: 0 2 1: 1 1 2: 1 2 3: 2 1 4: 3 0 5: 3 1 6: 4 0 7: 5 0 NEIGHBOR matrix: Row: 0 1 Col 0: 1 0 1: 1 1 2: 0 0 3: 1 0 4: 1 1 5: 0 0 6: 1 0 7: 0 0 4) Generalized grid in 2D: SPARSE_INDEX matrix: Row: 0 1 Col 0: 0 0 1: 0 1 2: 0 2 3: 0 3 4: 1 0 5: 1 1 6: 2 0 7: 3 0 NEIGHBOR matrix: Row: 0 1 Col 0: 1 1 1: 1 1 2: 0 1 3: 0 0 4: 1 1 5: 0 0 6: 1 0 7: 0 0 TEST03: Set up examples of the GG (Gerstner-Griebel) data structure for generalized sparse grids. 1) Isotropic grid in 2D Before Heap: I A G 0 3 3 1 6 3.2 2 8 3.3 3 9 3.1 After Heap: I A G 0 8 3.3 1 6 3.2 2 3 3 3 9 3.1 Transferring index 8 from active to old set. TEST04: Simulate incremental coefficient calculations. Generalized grid in 2D: SPARSE_INDEX matrix: Row: 0 1 Col 0: 0 0 COEF vector: 0: 1 --- - Sum: 1 SPARSE_INDEX matrix: Row: 0 1 Col 0: 0 0 1: 0 1 COEF vector: 0: 0 1: 1 --- - Sum: 1 SPARSE_INDEX matrix: Row: 0 1 Col 0: 0 0 1: 0 1 2: 0 2 COEF vector: 0: 0 1: 0 2: 1 --- - Sum: 1 SPARSE_INDEX matrix: Row: 0 1 Col 0: 0 0 1: 0 1 2: 0 2 3: 0 3 COEF vector: 0: 0 1: 0 2: 0 3: 1 --- - Sum: 1 SPARSE_INDEX matrix: Row: 0 1 Col 0: 0 0 1: 0 1 2: 0 2 3: 0 3 4: 1 0 COEF vector: 0: -1 1: 0 2: 0 3: 1 4: 1 --- - Sum: 1 SPARSE_INDEX matrix: Row: 0 1 Col 0: 0 0 1: 0 1 2: 0 2 3: 0 3 4: 1 0 5: 1 1 COEF vector: 0: 0 1: -1 2: 0 3: 1 4: 0 5: 1 --- - Sum: 1 SPARSE_INDEX matrix: Row: 0 1 Col 0: 0 0 1: 0 1 2: 0 2 3: 0 3 4: 1 0 5: 1 1 6: 2 0 COEF vector: 0: 0 1: -1 2: 0 3: 1 4: -1 5: 1 6: 1 --- - Sum: 1 SPARSE_INDEX matrix: Row: 0 1 Col 0: 0 0 1: 0 1 2: 0 2 3: 0 3 4: 1 0 5: 1 1 6: 2 0 7: 3 0 COEF vector: 0: 0 1: -1 2: 0 3: 1 4: -1 5: 1 6: 0 7: 1 --- - Sum: 1 TEST05: Predict new coefficients given candidate index. Spatial dimension M = 2 Number of items in active set N1 = 5 Index Coef Indices 0: 1 0 2 1: 1 1 1 2: 1 2 0 3: -1 0 1 4: -1 1 0 Candidate: 1 2 Index Coef Coef Old New 0: 1 0 1: 1 0 2: 1 1 3: -1 0 4: -1 -1 5: 1 -- ---- ---- Sum: 1 1 TEST06: Predict new coefficients given candidate index. Spatial dimension M = 2 Number of items in active set N1 = 5 Index Coef Indices 0: 1 2 0 1: 1 1 1 2: 1 0 2 3: -1 1 0 4: -1 0 1 Candidate: 3 0 Index Coef Coef Old New 0: 1 0 1: 1 1 2: 1 1 3: -1 -1 4: -1 -1 5: 1 -- ---- ---- Sum: 1 1 sandia_sgmgg_test(): Normal end of execution. 15 January 2023 08:09:41 PM